Dexter Horthy (CEO of Human Layer) argues that although coding agents got much better at solving problems in 2026, they did not get better at keeping codebases maintainable, so the "lights-off" software factory where nobody reads the code doesn't work yet. He backs this with SlopCodeBench, a University of Wisconsin benchmark that reveals models' code degrades as features accumulate (GPT-5.5 scored 14.8%), plus industry data showing code review quality down and incidents/bugs per PR up. He then lays out ~9 practices for an agentic "software factory" — plan before building, align visually, give agents back pressure, feed user feedback and pager alerts straight into PRs — and sketches the buy-or-build layers (compute, dev environment, harness, control plane) that Human Layer is targeting.
- A report cited from May showed that since teams adopted Opus 4.5, code review quality dropped, PRs increasingly skip review, and incidents and bugs per developer rose — which Horthy says is a tooling problem, not a skill issue.
- The software factory concept dates to 1968; the agentic version swaps the human builder for an agent, which compresses build time to minutes while review still takes hours or days, making review the new bottleneck.
- Core thesis: unattended models will not maintain or improve codebase quality over time, because telling a model what to fix requires understanding the codebase — which means it isn't unattended.
- Maintainability has no fast oracle, so reinforcement learning can't reward it; benchmarks reward passing tests, not good architecture, and the cost of bad architecture only shows up months later.
- SlopCodeBench discloses a problem in pieces and makes the model add features incrementally, mirroring real development; GPT-5.5 scored 14.8% on it while saturating other coding benchmarks near 95%.
- Steve Yegge, who spent a year telling people that reading code would leave them behind, now warns that unattended models write slop so complex they can't debug it themselves.
- Practical recommendations include planning proportional to expected pain, the open-source "show me" skill for visual alignment, giving agents browsers/curl to test their own work, Dylan Mulroy's ~100 TypeScript anti-slop rules, and attaching a candidate fix PR to every 3 a.m. page.
- Horthy frames "loops" as just forward pressure (what triggers new work) plus back pressure (feedback the agent can hill-climb on without a human), and proposes a centralized system of record for sessions, plans, and prompts.
A concrete, unsaturated benchmark result that directly contradicts the "coding is solved" narrative from terminal-bench style scores.
Instead of telling the model the whole problem to solve up front, it gives the model the challenges... in bits and makes it write the code and then do another feature and then do another feature, which maps much more closely to how everyone in this room builds software... GPT-5.5 was the best model on the market. It got a 14.8%.
A sharp reversal from one of the loudest voices for unattended coding, paired with the numbers showing maintainability gains are only a point or so per model generation.
Not only did he build Gas Town, he went around the internet telling people for a year that if you're still trying to read the code, you are going to fall behind... and here he is last week: if you don't pay attention to the models, they're going to write slop code. They're going to build something so complex that they themselves can't debug it.
Unattended models will not improve or maintain your code base quality over time.
Maintainability has no fast oracle. We don't find out that the code was ugly until two months later when someone is paged at 3:00 in the morning.
You would say, the code is slop, but that'll be GPT-7's problem. Folks, we're at GPT-6, and I don't think we've gotten that much better at this.